The Power of Artificial Intelligence on Drug Manufacturing and Clinical Trials

  • Bongs Lainjo
Keywords: Artificial Intelligence, Machine Learning, Drug Discovery, Drug Development, Clinical Trials, Pharmaceutical Industry, Healthcare, Ethics


Artificial intelligence (AI) and machine learning (ML) have become significant aspects of contemporary society. The prominence of AI in society is attributed to its vital role in different quotas of life, that is, by using "big data" to perform tasks that would be impossible or take long to be done by a human. These functions are achieved by perceiving, synthesizing, and inferring information performed by computerized machines instead of intelligence possessed by animals or humans. For example, in the pharmaceutical industry, AI technology is used to improve efficiency and accuracy in manufacturing drugs and their performance in improving health care. This study takes responsibility to look into aspects impacted by artificial intelligence in the modern pharmaceutical industry. Aspects studied herein include the impact of AI and the time taken to discover and develop drugs, the consumer cost of the drugs developed with AI/ML technology, its impact on medical education, and ethical issues associated with the related technology, notwithstanding the impacts of AI/ML on clinical trials. The study found that AI and ML significantly impact the time taken to discover drugs, and the technology in discussion contributed to consumer cost reduction. Furthermore, it has contributed to the need for revising the medical curriculum; even with the ethical concerns on the safety and privacy of data utilized in the technology, it has significantly led to significant changes in the clinical trials of drug discovery and development methodologies.


AbbVie. (2022). Everyone’s talking about data science and analytics. Here’s how AbbVie approaches it.
Ahmed, E. (2020). Google Cloud’s new AI suite hits on doctors’ admin headaches. Business Insider.
AstraZeneca. (2022, May 10). AstraZeneca.;,to%20deliver%20life%2Dchanging%20medicines.
Bajwa, F. (2019). Building the future of MedTech with AI.
Baron, J. (2012). Evolution of clinical research: A history before and beyond James Lind. Perspectives in Clinical Research, 3(4), 149.
Batta, A., Kalra, B. S., & Khirasaria, R. (2020). Trends in FDA drug approvals over last two decades: An observational study. Journal of Family Medicine and Primary Care, 9(1), 105–114.
Bender, A., & Cortés-Ciriano, I. (2020). Artificial intelligence in drug discovery: what is realistic, what are illusions? Part 1: Ways to make an impact and why we have yet to arrive. Drug Discovery Today, 26(2).
Bittner, M.-I., & Farajnia, S. (2022). AI in drug discovery: Applications, opportunities, and challenges. Patterns, 3(6), 100529.
Block, J. (2022). J&J Janssen unit, SRI International to collaborate on drug discovery using AI | Seeking Alpha.
Briganti, G., & Moine, O. L. (2020). Artificial Intelligence in Medicine: Today and Tomorrow. Frontiers in Medicine, 7,
Chen, Z., Liu, X., Hogan, W., Shenkman, E., & Bian, J. (2021). Applications of artificial intelligence in drug development using real-world data. Drug Discovery Today, 26(5), 1256–1264.
Farhud, D. D., & Zokaei, S. (2021). Ethical Issues of Artificial Intelligence in Medicine and Healthcare. Iranian Journal of Public Health.
Fleming, N. (2018). How artificial intelligence is changing drug discovery. Nature, 557(7707), S55–S57.
Frommeyer, T. C., Fursmidt, R. M., Gilbert, M. M., & Bett, E. S. (2022). The Desire of Medical Students to Integrate Artificial Intelligence into Medical Education: An Opinion Article. Frontiers in Digital Health, 4.
Gerke, S., Minssen, T., & Cohen, I. G. (2020). Ethical and Legal Challenges of Artificial Intelligence-Driven Health Care. SSRN Electronic Journal.
GlaxoSmithKline. (2021). AI and ML power better predictions for patient impact | GSK.
Hariry, R. E., Barenji, R. V., & Paradkar, A. (2022). Towards Pharma 4.0 in clinical trials: A future-orientated perspective. Drug Discovery Today, 27(1), 315–325.
Hughes, J., Rees, S., Kalindjian, S., & Philpott, K. (2011). Principles of Early Drug Discovery. British Journal of Pharmacology, 162(6), 1239–1249.
Johnson, K. B., Wei, W., Weeraratne, D., Frisse, M. E., Misulis, K., Rhee, K., Zhao, J., & Snowdon, J. L. (2020). Precision Medicine, AI, and the Future of Personalized Health Care. Clinical and Translational Science, 14(1).
Kahn, J. (2021). Money is pouring into A.I.-assisted drug discovery, while fewer AI startups are getting VC backing. Fortune.
Kelle, U. (2008). Combining qualitative and quantitative research methods to support psychosocial and mental health programmes in complex emergencies. Intervention, 6(3), 348.
Kiriiri, G. K., Njogu, P. M., & Mwangi, A. N. (2020). Exploring different approaches to improve the success of drug discovery and development projects: a review. Future Journal of Pharmaceutical Sciences, 6(1).
Kolluri, S., Lin, J., Liu, R., Zhang, Y., & Zhang, W. (2022). Machine Learning and Artificial Intelligence in Pharmaceutical Research and Development: a Review. The AAPS Journal, 24(1).
Kulkov, I. (2021). The role of artificial intelligence in business transformation: A case of pharmaceutical companies. Technology in Society, 66, 101629.
Liebman, M. (2022). The Role of Artificial Intelligence in Drug Discovery and Development. Chemistry International, 44(1), 16–19.
Liu, Z., Roberts, R. A., Lal-Nag, M., Chen, X., Huang, R., & Tong, W. (2021). AI-based language models powering drug discovery and development. Drug Discovery Today, 26(11), 2593–2607.
Londhe, V. Y., & Bhasin, B. (2019). Artificial intelligence and its potential in oncology. Drug Discovery Today, 24(1), 228–232.
Merck. (2022). Merck Announces the Launch of the Merck Digital Sciences Studio to Help Healthcare Startups Quickly Bring their Innovations to Market.
Novartis. (2021). The art of drug design in a technological age. Novartis.
NW, 1615 L. S., Suite 800Washington, & Inquiries, D. 20036USA202-419-4300 | M.-8.-8. | F.-4.-4. | M. (2020, June 30). 5. Tech causes more problems than it solves. Pew Research Center: Internet, Science & Tech.
NW, 1615 L. S., Suite 800Washington, & Inquiries, D. 20036USA202-419-4300 | M.-8.-8. | F.-4.-4. | M. (2021, June 16). 1. Worries about developments in AI. Pew Research Center: Internet, Science & Tech.
Patel, V., & Shah, M. (2021). A comprehensive study on artificial intelligence and machine learning in drug discovery and development. Intelligent Medicine, 2(3).
Paul, D., Sanap, G., Shenoy, S., Kalyane, D., Kalia, K., & Tekade, R. K. (2020). Artificial intelligence in drug discovery and development. Drug Discovery Today, 26(1). NCBI. (2021). Artificial Intelligence: On a mission to Make Clinical Drug Development Faster and Smarter | Pfizer.
Pharmaceutical Technology. (2021, August 19). BMS to in-license Exscientia’s AI-driven drug candidate. Pharmaceutical Technology.
Radin, A. (2017). Artificial Intelligence in Drug Discovery: An Evolution, Not a Revolution. Drug Discovery from Technology Networks. (2022). Roche | Harnessing the power of AI.
Sanofi. (2022). Exscientia and Sanofi establish strategic research collaboration to develop an AI-driven pipeline of precision-engineered medicines - Sanofi.
Vamathevan, J., Clark, D., Czodrowski, P., Dunham, I., Ferran, E., Lee, G., Li, B., Madabhushi, A., Shah, P., Spitzer, M., & Zhao, S. (2019). Applications of machine learning in drug discovery and development. Nature Reviews Drug Discovery, 18(6), 463–477.
Wong, C. H., Siah, K. W., & Lo, A. W. (2018). Estimation of clinical trial success rates and related parameters. Biostatistics, 20(2), 273–286.
Wouters, O. J., McKee, M., & Luyten, J. (2020). Estimated Research and Development Investment Needed to Bring a New Medicine to Market, 2009-2018. JAMA, 323(9), 844.
How to Cite
Lainjo, B. (2023). The Power of Artificial Intelligence on Drug Manufacturing and Clinical Trials. European Journal of Science, Innovation and Technology, 3(3), 1-15. Retrieved from